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Testing two-step models of negative quantification using a novel machine learning analysis of EEG.

The sentences "More than half of the students passed the exam" and "Fewer than half of the students failed the exam" describe the same set of situations, and yet the former results in shorter reaction times in verification tasks. The two-step model explains this result by postulating that negative q...

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Published in:Language, Cognition & Neuroscience Vol. 39; no. 5; pp. 632 - 657
Main Authors: Ramotowska, S., Archambeau, K., Augurzky, P., Schlotterbeck, F., Berberyan, H.S., Van Maanen, L., Szymanik, J.
Format: pictorial research tables/charts Journal Article
Published: Taylor & Francis Ltd Jun2024
Online Access:View this record in EBSCOhost
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      jtl: Language, Cognition & Neuroscience
      issn: 23273798
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      dt: Jun2024
      vid: 39
      iid: 5
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      pub: Taylor & Francis Ltd
      place: Philadelphia, Pennsylvania
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        10.1080/23273798.2024.2345302
        177396189
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        atl: Testing two-step models of negative quantification using a novel machine learning analysis of EEG.
      aug:
        au:
          Ramotowska, S.
          Archambeau, K.
          Augurzky, P.
          Schlotterbeck, F.
          Berberyan, H.S.
          Van Maanen, L.
          Szymanik, J.
        affil: Institute for Logic, Language and Computation, University of Amsterdam, Amsterdam, The Netherlands
      sug:
        subj:
          Machine Learning
          Electroencephalography Methods
          Reaction Time
          Task Performance and Analysis
          Language Processing
          Cognition
          Human
          Funding Source
          Neurosciences
          Semantics
          Reading
          Word Lists
          Exploratory Research
          Multivariate Analysis
          Nonparametric Statistics
          T-Tests
          Descriptive Statistics
      ab: The sentences "More than half of the students passed the exam" and "Fewer than half of the students failed the exam" describe the same set of situations, and yet the former results in shorter reaction times in verification tasks. The two-step model explains this result by postulating that negative quantifiers contain hidden negation, which involves an extra processing stage. To test this theory, we applied a novel EEG analysis technique focused on detecting cognitive stages (HsMM-MVPA) to data from a picture-sentence verification task. We estimated the number of processing stages during reading and verification of quantified sentences (e.g. "Fewer than half of the dots are blue") that followed the presentation of pictures containing coloured geometric shapes. We did not find evidence for an extra step during the verification of sentences with fewer than half. We provide an alternative interpretation of our results in line with an expectation-based pragmatic account.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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